Mimo receiver and method for receiving spatially-multiplexed ofdm signals

ABSTRACT

In a multiple-input multiple-output (MIMO) system, multiple receive antennas produce a received signal vector, Y, which includes an element for each of the receive antennas. In an embodiment of a de-mapping method performed within a MIMO receiver, a quadrature phase shift keying (QPSK) search is performed within a search space that includes the full constellation of symbol points. Based on the results of the QPSK search, the search space is reduced to fewer than all of the quadrants, and the received signal vector data is scaled and transformed to the reduced search space. A lower-level QPSK search is performed, and the process is repeated until the modulation order is reduced to a QPSK constellation. Hard or soft decisions corresponding to the search results may then be passed to a decoder.

This application is a continuation of U.S. patent application Ser. No.12/276,834, filed on Nov. 24, 2008, which is a continuation of U.S.patent application Ser. No. 11/844,200, filed on Aug. 23, 2007, nowissued as U.S. Pat. No. 7,457,376, which is a continuation of U.S.patent application Ser. No. 10/750,169, filed on Dec. 31, 2003, nowissued as U.S. Pat. No. 7,308,047, which are incorporated herein byreference in their entireties.

TECHNICAL FIELD

The inventive subject matter pertains to data communications and, moreparticularly, to receiver apparatus and symbol de-mapping methods inmultiple-input multiple-output (MIMO) systems.

BACKGROUND

Due to an ever-increasing demand for wireless communication services,system developers continually strive to increase the capacities ofwireless systems. This is particularly true, for example, in cellulartelephone systems and wireless local area network (WLAN) systems. Toincrease system capacities, multiple-input multiple-output (MIMO)technologies are being developed for cellular telephone and WLANapplications.

In a MIMO system, a MIMO transmitter includes multiple transmit antennasfor data transmission, and a MIMO receiver includes multiple receiveantennas for data reception. When signals are simultaneously transmittedby multiple antennas that are spaced more than a coherence distanceapart, the signals will each have distinct spatial signatures. Thecoherence distance is the minimum spatial separation of antennas forindependent fading, and its value depends on the angle spread of themulti-paths arriving at or departing from an antenna array. A MIMOsystem may provide for increased system capacity and/or quality,compared with known technologies, by exploiting the spatial diversitybetween the multiple antennas within an antenna array. MIMO systemdevelopers continue to try to increase system capacities by developingMIMO processing technologies that yield acceptable system performance.

BRIEF DESCRIPTION OF THE DRAWINGS

The appended claims point out, with particularity, different embodimentsof the inventive subject matter described herein. However, the detaileddescription presents a more complete understanding of variousembodiments of the inventive subject matter when considered inconnection with the figures, wherein like-reference numbers refer tosimilar items throughout the figures and:

FIG. 1 is a simplified diagram illustrating multi-path communicationsbetween a MIMO transmitter and a MIMO receiver, in accordance with anembodiment of the invention;

FIG. 2 is a simplified block diagram of a MIMO device capable ofmodulating and transmitting a symbol stream using spatial-multiplexingtechniques, in accordance with an embodiment of the invention;

FIG. 3 is a simplified block diagram of a MIMO device capable ofreceiving, de-modulating, and de-mapping spatially-multiplexed,radio-frequency signals, in accordance with an embodiment of theinvention;

FIG. 4 illustrates a four-point QPSK (quadrature phase shift keying)constellation pattern;

FIG. 5 illustrates a 16 QAM (quadrature amplitude modulation)constellation pattern;

FIG. 6 illustrates a 64 QAM constellation pattern;

FIG. 7 illustrates bit-hierarchical MIMO de-mapping of a single receivedvector element within a 16 QAM constellation, in accordance with anembodiment of the invention;

FIG. 8 is a flowchart of a procedure for performing bit-hierarchicalMIMO de-mapping, in accordance with an embodiment of the invention; and

FIG. 9 is an example of a tree diagram, which depicts a tree-searchingalgorithm that can be incorporated into various embodiments of theinvention.

DETAILED DESCRIPTION

Various embodiments of the inventive subject matter described hereininclude methods and apparatus for de-mapping and de-modulatingmultiple-input multiple-output (MIMO) symbols. Embodiments of theinventive subject matter may be referred to individually and/orcollectively herein by the term “invention.” Use of this term is merelyfor convenience and is not intended to voluntarily limit the scope ofthis application to any single invention or inventive concept if morethan one is disclosed.

Examples of various electronic systems and devices in which embodimentsof the invention can be incorporated include, but are not limited to,wireless local area network (WLAN) systems, cellular telephone systems,radio networks, computers (e.g., desktop, laptop, hand-held, server,etc.), and wireless communication devices (e.g., cellular telephones,pagers, radios, etc.), to name a few. Embodiments of the invention couldbe used in other types of systems and/or devices, as well, as would beapparent to one of skill in the art based on the description herein. Theinventive subject matter described herein is not intended to be limitedto those systems and devices that are described herein.

FIG. 1 is a simplified diagram illustrating multi-path communicationsbetween MIMO devices 102, 106, in accordance with an embodiment of theinvention. Although only two devices 102, 106 are illustrated, a MIMOsystem can include a plurality of devices 102, 106. A device 102, 106may be mobile, portable or stationary. One or more devices 102, 106 maybe included within a network access point, a portable or stationarycomputer (e.g., a laptop, desktop or server computer), a cellulartelephone, a handheld radio, or numerous other types of devices havingthe ability to perform simplex or duplex communications with otherdevices over a wireless medium.

Each device 102, 106 may include a transmitter, a receiver or both.Where devices 102, 106 include both a transmitter and a receiver, duplexcommunications can be supported. For purposes of description, device 102is referred to, below, as a transmitter, and device 106 is referred toas a receiver. However, it is to be understood that devices 102, 106also can include one or more receivers and transmitters, respectively.The detailed description herein discusses an example of a single-usercommunication model with a point-to-point link between the transmitter102 and receiver 106.

As discussed previously, a MIMO system exploits spatial diversity withinits antenna arrays to increase system capacity and/or signal quality. Inthe example system illustrated in FIG. 1, transmitter 102 is equippedwith a number, n_(T), of transmit antennas 104, and receiver 106 isequipped with a number, n_(R), of receive antennas 108. The number oftransmit antennas and the number of receive antennas may or may not beequal.

Transmitter 102 sends radio-frequency (RF) signals 110, 112, 114 toreceiver 106 over a “channel,” which typically includes the medium offree space. The input-output relationship of the n_(R)×n_(T) matrixchannel is represented by equation (1) as follows:

Y=Hx+N  (1)

where Y=[y₀y₁ . . . y_(n) _(R-1) ]^(T) is the n_(R)×1 receive signalvector, H is the n_(R)×n_(T) channel transfer matrix, x=[x₀x₁ . . .x_(n) _(T-1) ]^(T) is the n_(T)×1 transmit signal vector, and N is anoise vector.

Often, it is the case that the channel transfer matrix is unknown attransmitter 102, but it may be nearly perfectly known and tracked atreceiver 106. Channel knowledge at transmitter 102 can be obtainedthrough receiver feedback and/or the use of transmit-receive,duplexing-based channel mapping methods.

One MIMO technique that is used to increase system capacity is referredto as “spatial-multiplexing.” The idea of spatial-multiplexing is thatthe use of multiple antennas at the transmitter and the receiver, inconjunction with rich scattering in the propagation environment, opensup multiple data pipes within the same frequency band. At thetransmitter, an input symbol stream is split into multiple independent,lower-rate sub-streams. These sub-streams are modulated to form distinctsignals, which are transmitted on separate transmit antennas. If thetransmit antennas are separated in space sufficiently, and if thewireless channel has sufficient multi-path characteristics, then eachtransmitted symbol sub-stream induces a different spatial signature on areceiver antenna array. If the spatial signatures of the signals inducedat the receiver antennas are well separated, then the receiver canseparate the multiple transmitted signals to yield estimates of thesub-streams. The sub-streams are then re-combined to form an estimate ofthe original symbol stream. The use of spatial-multiplexing yields apotentially linear (i.e., in the number of antennas) increase incapacity.

The modulation symbols typically map to a standard constellation, suchas BPSK (bipolar phase shift keying) or a rectangular QAM (quadratureamplitude modulation) constellation. Rectangular QAM constellationsinclude, for example, QPSK (quadrature phase shift keying), 16 QAM, 64QAM, 256 QAM, and the like. Using rectangular QAM modulation, thetransmit signal vector, x, and the receive signal vector, Y, are vectorsof complex modulation symbols.

FIG. 2 is a simplified block diagram of a MIMO device 200 capable ofencoding, modulating, and transmitting a symbol stream usingspatial-multiplexing techniques, in accordance with an embodiment of theinvention. In one embodiment, device 200 includes an information bitsource 202, an encoder 204, a de-multiplexer 206, and multiple antennasubsystems 208, 210, 212. Although three antenna subsystems 208, 210,212 are illustrated in FIG. 2, more or fewer antenna subsystems can beincluded, in other embodiments.

Information bit source 202 produces a bit stream 230. Information bitsource 202 can be a higher-level layer of a communications architecture(e.g., a medium access control (MAC) layer) or a bit source of anothertype. Information bit source 202 can include, for example, one or moregeneral-purpose or special-purpose processors, application-specificintegrated circuits (ASICs), multi-chip modules, combinations thereof,or other devices.

Bit stream 230 can be continuous or intermittent. Bit stream 230 caninclude a variety of different types of information, and the informationcan be uncompressed or compressed, unencrypted or encrypted, and/orpreviously subjected to any of a number of packetizing and/or processingtechniques. In one embodiment, for example, bit stream 230 can includetime-division multiple access (TDMA) frames for a multi-userapplication.

Bit stream 230 is received by encoder 204, which adds redundancy to theinformation bits to enable detection and correction of bit errors at thereceiver. For example, encoder 204 may perform forward error correction(FEC) encoding, among other encoding techniques. Encoder 206 produces acoded bit sequence 232.

The coded bit sequence 232 is received by de-multiplexer 206.De-multiplexer 206 produces n_(T) (i.e., the number of transmitantennas) space channels 234, 236, 238, which are sub-streams of thecoded bit sequence 232. Each of these sub-streams 234, 236, 238 caninclude different information. The sub-streams 234, 236, 238 areprovided to the multiple antenna subsystems 208, 210, 212, respectively.

Antenna subsystems 208, 210, 212 modulate and simultaneously transmitthe information within sub-streams 234, 236, 238 within the samefrequency band. Antenna subsystems 208, 210, 212 can use a variety ofdifferent modulation techniques including, but not limited to,narrowband modulation, OFDM (orthogonal frequency-divisionmultiplexing), and CDMA (code-division multiple access), to name a few.

In one embodiment, each transmit antenna subsystem 208, 210, 212includes an interleaver 214, a bit-to-symbol mapper 216, a modulator218, and an antenna 220. In another embodiment, an interleaver and/or abit-to-symbol mapper can be included in the transmitter between encoder204 and de-multiplexer 206, rather than within each antenna subsystem208, 210, 212.

Interleaver 214 receives the coded sub-stream 234 from de-multiplexer206. Interleaver 214 then permutates the order of the bits, in order tomake the transmitted signal more robust.

Bit-to-symbol mapper 216 receives the interleaved sub-stream, and itmaps the bits of the sub-stream to a series of symbols. Each symbolcorresponds to a set of one or more bits, and each symbol can berepresented by a symbol vector. The mapping process depends upon thetype of symbol constellation used, and upon the number of points in theconstellation. In one embodiment, the symbol vectors are complex vectorsthat are encoded using BPSK or one of a variety of rectangular QAMtechniques including, but not limited to, QPSK, 16 QAM, 64 QAM, 256 QAM,or the like. In an alternate embodiment, the symbol vectors are simplevectors that are encoded using a PAM (pulse amplitude modulation)technique. Various symbol constellation examples are described later, inaccordance with FIGS. 4-6.

In one embodiment, the symbol vectors are represented by complexnumbers, where each has a phase and an amplitude component. Thesecomplex symbol vectors are passed to modulator 218. Modulator 218converts the symbol vector values into an RF waveform. Accordingly,modulator 218 applies a modulation procedure (e.g., OFDM or CDMA),converts the modulated signals into the analog time domain (e.g., usingan inverse Fast Fourier Transform (FFT)), performs various filtering andamplification procedures, and up-converts the signal to an RF frequency.

At least a portion of the modulator architecture depends on themodulation technology employed. For example, if OFDM is used to modulatethe symbols, each modulator 218 can include a serial-to-parallel(S-to-P) converter (not shown), which takes a number of vectors from theincoming symbol vector stream and produces multiple output symbolscorresponding to the OFDM sub-band channels that are applied to an IFFT(Inverse FFT) to create a time domain signal. For a CDMA system, themodulation symbols are modulated onto a coded waveform. For othermodulation techniques, other modulator architectures can be used, aswould be obvious to one of skill in the art based on the descriptionherein.

The RF waveform produced by modulator 218 is provided to antenna 220,which transmits the RF signal 240 over the air interface. Each of theother antenna subsystems 210, 212 also produce and transmit RF signals242, 244 over the air interface. The signals 240, 242, 244 occupy thesame frequency band (i.e., they are co-channel signals). If the transmitantennas (e.g., antenna 220) are appropriately spaced, then signals 240,242, 244 will each have distinct spatial signatures.

A MIMO receiver, which is described in more detail in conjunction withFIG. 3, includes multiple receive antennas. Each receive antennaobserves a different, noisy superimposition of faded versions of then_(T) transmitted signals 240, 242, 244. Part of the complexity of MIMOcommunications results from the fact that, at the receiver, asubstantial amount of cross-talk can exists between the multiple-datapipes. In a spatial-multiplexing system, the receiver determines theconstituent symbol sub-streams, and it produces an estimate of theoriginal symbol stream.

Several different types of linear and non-linear MIMO receivers existfor the purpose of transforming received signal vectors into estimatesof transmitted symbol streams. These receiver types include zero-forcingreceivers, minimum mean-square error (MMSE) receivers, successiveinterference canceling (SIC) receivers (e.g., Bell Labs LAyeredSpace-Time (BLAST) and V-BLAST), maximum likelihood (ML) receivers, andreduced complexity ML receivers, such as sphere decoders.

Each type of receiver has different performance-versus-complexitytradeoffs. For example, linear zero-forcing and MMSE receiversexperience significant noise enhancement, and thus these types ofreceivers are not widely used in MIMO systems. The principles underlyingnon-linear ML and SIC receivers are discussed briefly below, as thesetypes of receivers can perform more favorably in a MIMO setting.

An ML receiver applies the “ML rule” in order to de-modulate a set ofsuperimposed MIMO symbols. The ML rule is represented by equation (2) asfollows:

$\begin{matrix}{\hat{x} = {\underset{x}{argmin}{{Y - {Hx}}}^{2}}} & (2)\end{matrix}$

where {circumflex over (x)}=[{circumflex over (x)}₀{circumflex over(x)}₁ . . . {circumflex over (x)}_(n) _(T-1) ]^(T) is an estimate of then_(T)×1 transmit signal vector, Y=[y₀y₁ . . . y_(n) _(R-1) ]^(T) is then_(R)×1 receive signal vector, H is the n_(R)×n_(T) channel transfermatrix, and x=[x₀x₁ . . . x_(n) _(T-1) ]^(T) is the n_(T)×1 transmitsignal vector. Using QAM modulation, {circumflex over (x)}, Y, and x arevectors of complex modulation symbols.

Using the ML rule, the number of possible MIMO symbols x equals M^(n)^(T) , where M is the number of points in the modulation constellation.For example, a 4×4 16 QAM system (i.e., a 16 QAM system withn_(T)=n_(R)=4) has 16⁴=65,536 possible MIMO symbol values. Using a fullML search, the number of symbol values is proportional to the number ofcomputations that are performed to reach a solution. Accordingly, asignificant disadvantage to full ML de-modulation is that it requires alarge number of computations in order to de-modulate symbols that havebeen modulated using higher-order modulation schemes.

An alternative to ML de-mapping is de-mapping using a SIC algorithm,such as the BLAST or V-BLAST algorithms (referred to collectively as the“BLAST algorithms”). The BLAST algorithms are based on a zero-forcing orMMSE estimator, but with modifications. Using the BLAST algorithmtechniques, a strongest symbol (i.e., a symbol with the lowestestimation error variance) is estimated. That symbol is then de-mapped(i.e., the estimated vector is correlated with the nearest constellationpoint, and the data bits corresponding to the point are obtained). Theresulting data bits are then re-mapped to a modulation symbol, and thechannel matrix, H, is applied to the remodulated signal. The resultingvector is subtracted from the received vector, Y. The dimension of x isthen reduced, a column of H is deleted, and the process is repeated forthe next-strongest symbol, until all superimposed symbols have beende-mapped.

Fewer computations need to be performed in order to find a solutionusing the BLAST algorithms, as opposed to using ML de-mapping. However,the error propagation characteristics of the BLAST algorithms can resultin decreased performance, when compared with ML de-mapping.

Embodiments of the invention include de-modulation and de-mappingmethods that are less computationally complex than full ML de-mapping.In addition, embodiments of the invention include de-modulation andde-mapping methods that can perform better than BLAST algorithmde-modulation techniques. The de-modulation and de-mapping methods ofthe various embodiments are referred to herein as “bit-hierarchical”(BH) MIMO de-mapping methods. The term “bit-hierarchical” is used,herein, because embodiments of the invention exploit a hierarchicalfeature of certain modulations, which is that the modulation can bedecomposed into a hierarchal sequence of elementary modulations, with anatural order to the hierarchy. One embodiment of the invention can beapplied to QAM with QPSK as the elementary modulation. However, anotherembodiment of the invention can be applied to PAM with BPSK as theelementary modulation. A BH MIMO de-mapping method, in accordance withthe various embodiments, is carried out in a MIMO device that includes aMIMO receiver.

FIG. 3 is a simplified block diagram of a MIMO device 300 capable ofreceiving and de-modulating spatially-multiplexed, RF signals, inaccordance with an embodiment of the invention. In one embodiment,device 300 includes an information bit destination 302, a channeldecoder 304, a multiplexer 306, and multiple antenna subsystems 308,310, 312. Although three receive antenna subsystems 308, 310, 312 areillustrated, more or fewer antenna subsystems can be included, in otherembodiments.

Each of the n_(R) antenna subsystems 308, 310, 312 receives an RF signal322, 324, 326, which include different noisy superimpositions of fadedversions of the n_(T) transmitted signals (e.g., signals 240, 242, 244,FIG. 2). In accordance with various embodiments, each receive antennasubsystem 308, 310, 312 then de-modulates the received signals 322, 324,326 and applies a BH MIMO de-mapping technique.

In one embodiment, each receive antenna subsystem 308, 310, 312 includesan antenna 314, a de-modulator 316, a symbol de-mapper 318, and ade-interleaver 320. In another embodiment, a symbol de-mapper and/orde-interleaver can be included in the receiver between decoder 304 andmultiplexer 306, rather than within each antenna subsystem 308, 310,312. Signal processing through one antenna subsystem 308 is describedbelow. It is to be understood that other antenna subsystems 310, 312 cansimultaneously perform similar processing.

Antenna 314 receives RF signal 322 from the wireless channel.De-modulator 316 amplifies the RF signal, and it downconverts the signalfrom an RF frequency to an intermediate frequency or to baseband.De-modulator 316 also converts the signal from the analog domain to thedigital domain (e.g., using an FFT). Various filtering procedures canalso be performed.

De-modulator 316 further converts the digital signal into a series ofreceived symbol vector representations. This portion of the de-modulatorarchitecture depends on the modulation technology employed. For example,if OFDM is used to de-modulate the symbols, each de-modulator 316 caninclude a serial-to-parallel (S-to-P) converter (not shown), whichapplies multiple input samples to an FFT, producing the OFDM sub-bandchannels, and which produces a number of vectors as an output vectorstream. For other modulation techniques, such as CDMA, for example,other de-modulator architectures can be used, as would be obvious to oneof skill in the art based on the description herein.

Symbol de-mapper 318 is a symbol-processing element, which receives thereceived symbol vectors. Based on these vectors, symbol de-mapper 318performs BH MIMO de-mapping, in accordance with various embodiments ofthe invention, which are described in detail, below. BH MIMO de-mappingproduces an estimate of the n_(T)×1 transmit signal vectors, which isrepresented as {circumflex over (x)}=[{circumflex over (x)}₀{circumflexover (x)}₁ . . . {circumflex over (x)}_(n) _(T-1) ].

In one embodiment, symbol de-mapper 318 further slices the estimatedsignal vectors to obtain the data bits corresponding to each of thesliced vectors. These “hard decisions” regarding the data bit values arepassed to de-interleaver 320, and ultimately to decoder 304.

In another embodiment, symbol de-mapper 318 instead produces “softdecisions” regarding the data bit values, and these soft decisions arestored within registers as a set of per bit log-likelihood ratios(LLRs), approximations of LLRs, or other soft-decision indicators. Thesesoft decision values are made available to decoder 304, which makes thefinal bit value determinations. Details regarding the BH MIMO de-mappingmethods of the various embodiments are provided in detail, below, inconjunction with FIGS. 7-9.

In one embodiment, de-interleaver 320 receives the data bit values orthe soft data bit values from symbol de-mapper 318. De-interleaver 320then reverses the interleaving process that was performed by thetransmitter. The de-interleaved data bit values are passed as asub-stream 328 to multiplexer 306.

Multiplexer 306 combines the multiple sub-streams 328, 330, 332 receivedfrom the various receive antenna subsystems 308, 310, 312 in a mannerconsistent with the de-multiplexing that was performed by thetransmitter. This results in a serial stream of data bits 334, which arepassed to decoder 304.

Decoder 304 receives the serial bit stream 334, in one embodiment. In analternate embodiment, decoder 304 receives the soft-decision values(e.g., LLRs, approximations of LLRs, or other soft-decision values).Decoding can include, for example, FEC decoding and/or other decodingtechniques. The processes performed by decoder 304 depend on how thedata was encoded in the transmitter (e.g., transmitter 200, FIG. 2),prior to transmission over the channel.

Information bit destination 302 receives the decoded bit stream 336, andit consumes, modifies, stores, and/or sends the information to one ormore different processing elements or devices. Information bitdestination 302 can be, for example but not by way of limitation, a MAClayer of a device. Information bit destination 302 can include, forexample, one or more general-purpose or special-purpose processors,ASICs, multi-chip modules, combinations thereof, or other devices. Thereceiver architecture of FIG. 3 can be used to perform BH MIMOde-modulation and de-mapping, in accordance with various embodiments.De-modulation and de-mapping can be performed for a number of differentmodulation constellation types. For example, but not by way oflimitation, various embodiments can be used to de-modulate and de-mapdata modulated into PAM constellations (e.g., BPSK) or rectangular QAMconstellations including, but not limited to, QPSK, 16 QAM, 64 QAM, 256QAM, and the like. FIGS. 4-6 illustrate QPSK, 16 QAM, and 64 QAMconstellations, respectively. These figures are not intended to limitapplication of the various embodiments to the illustratedconstellations, but instead are included to facilitate explanation ofthe inventive subject matter.

Using BPSK or QPSK modulation, the phase of a carrier signal variesbased upon the value of the data to be transmitted. For example, abinary 1 might be transmitted by generating a 180-degree phase shift inthe carrier, whereas a binary 0 could be represented by a 0-degree phaseshift. The term “quadrature” in “quadrature amplitude modulation” and“quadrature phase shift keying” comes from the carrier's ability toshift into one of four possible phase ranges (i.e., 0-90, 90-180,180-270, and 270-360 degrees) based on bit values of the data to betransmitted.

FIG. 4 illustrates a four-point QPSK constellation pattern 400. Eachpoint in the pattern resides in one of four quadrants 402, 404, 406,408, and each point can be represented by a complex symbol vector.Because the constellation includes four points, the constellation can beused to encode four dibit combinations. The dibit combination thatcorresponds to a particular point can be determined through amapping/de-mapping process. For example, the constellation pointresiding in quadrant 402 can correspond to a dibit value of “00,” asillustrated in FIG. 4. Other example 2-bit mappings are illustrated inFIG. 4 in association with each constellation point.

FIG. 5 illustrates a 16 QAM constellation pattern 500. 16 QAM modulationuses various combinations of phase shifts and amplitudes to produce apattern 500 that includes four points per quadrant 502, 504, 506, 508.Each of the 16 total points can be mapped to a specific 4-bitcombination. Various 4-bit mappings are illustrated in FIG. 5 inassociation with each constellation point.

FIG. 6 illustrates a 64 QAM constellation pattern 600. 64 QAM modulationuses various combinations of phase shifts and amplitudes to produce apattern 600 that includes 16 points per quadrant 602, 604, 606, 608. Inthis case, each of the 64 points can be mapped to a specific 6-bitcombination. Various 6-bit mappings are illustrated in FIG. 6, inassociation with each constellation point.

The methods and apparatus of the various embodiments are described inconjunction with rectangular QAM modulations (e.g., QPSK, 16 QAM, 64QAM, etc.), although the methods and apparatus can be applied to BPSKmodulations, as well. The parameter, m, is used herein to indicate themodulation order. The number of signal constellation points is 4^(m).Thus, m=1 is QPSK, m=2 is 16 QAM, m=3 is 64 QAM, and so on.

One MIMO symbol will transmit n_(T)4^(m) bits. These bits can be orderedin 2m vectors according to equations (3):

$\begin{matrix}{{i_{k} = {{\begin{bmatrix}\begin{matrix}i_{k,0} \\\vdots\end{matrix} \\i_{k,n_{T}}\end{bmatrix}\mspace{14mu} {and}\mspace{14mu} q_{k}} = \begin{bmatrix}\begin{matrix}q_{k,0} \\\vdots\end{matrix} \\q_{k,n_{T}}\end{bmatrix}}},{k = 0},\ldots \mspace{14mu},{m - 1}} & (3)\end{matrix}$

QPSK vectors are defined according to equation (4):

$\begin{matrix}{{x_{k}\left( {i_{k},q_{k}} \right)} = \begin{bmatrix}{\left( {{2i_{k,0}} - 1} \right) + {j\left( {{2q_{k,0}} - 1} \right)}} \\\vdots \\{\left( {{2i_{k,{n_{T} - 1}}} - 1} \right) + {j\left( {{2q_{k,{n_{T} - 1}}} - 1} \right)}}\end{bmatrix}} & (4)\end{matrix}$

Each of the elements of the QPSK vectors are ±1±j, in one embodiment.Accordingly, the QAM MIMO symbols can be written as equation (5):

x(i ₀ ,q ₀ , . . . ,i _(m-1) ,q _(m-1))

=2^(m-1) Δx ₀(i ₀ ,q ₀)+2^(m-2) Δx ₁(i ₁ ,q ₁)+ . . . +Δx _(m-1)(i_(m-1) ,q _(m-1))  (5)

where 2Δ is the free Euclidean distance of the QAM constellation (thatis, the distance between nearest neighbor constellation points). Variousconstellations can be written in this format, although actual bitmappings involve a transformation to the i and q vectors.

Methods of the various embodiments include a sequence of decisions,followed by interference cancellation. However, unlike prior-art SICalgorithms, which de-map modulation symbols sequentially, methods of thevarious embodiments perform sequential elemental searches (e.g., QPSKsearches) to de-map vectors of elementary modulation symbols x₀, x₁, x₂,. . . (e.g., QPSK symbols). In other words, methods of the variousembodiments de-modulate higher-order bits of all modulation symbols,cancel interference to reduce the modulation order, and repeat thisprocess until the modulation order is reduced to the elementalconstellation.

The basic method of various embodiments of the invention can berepresented by the following pseudo-code:

Initialize {tilde over (Y)}⁻¹ = (2^(m−1)Δ)⁻¹ Y and {tilde over (x)}⁻¹ =0; (6) for (k=0; k<m; k++) { {tilde over (Y)}_(k) = ½({tilde over(Y)}_(k−1) − {tilde over (x)}_(k−1)); (7)${{\hat{x}}_{k} = \left. \underset{{QPSK}\mspace{14mu} {vectors}\mspace{14mu} x}{\arg \mspace{14mu} \min}||{{\overset{\sim}{Y}}_{k} - {Hx}} \right.||^{2}};$(8) }where {tilde over (Y)}_(k) is a scaled version of the received signalvector at each search level k, {circumflex over (x)}_(k) is the QPSKvector at each search level k, H is the channel transfer matrix, and xis the transmit signal vector. As will be described in more detailbelow, equation (6) represents an initialization process, equation (7)cancels higher-order interference and scales the received signal vectordata, and equation (8) represents a level-k QPSK search.

As the above algorithm indicates, the number of points searched in orderto arrive at a result is substantially less than the number of pointssearched when using a full ML search. For the basic algorithm given inequations (6-8), the number of search points is approximately m4^(n)^(T) , as opposed to 4^(mn) ^(T) for a full ML search. For example, forn_(T)=4 and m=2 (i.e., 16 QAM), a full ML search will search 65,536points. A basic search, in accordance with an embodiment of theinvention, completes this search with approximately 512 points.Accordingly, a substantial reduction in the number of search points isachieved using methods of various embodiments of the invention.

FIG. 7 illustrates BH MIMO de-mapping of a single received vectorelement within a 16 QAM constellation 700, in accordance with anembodiment of the invention. Although FIG. 7 is a two-dimensionalconstellation representation, it is to be understood that the figuredepicts an example for de-mapping one element of a received signalvector, Y.

In a MIMO system, the received signal vector, Y, includes a number ofvector elements equal to the number of transmit antennas. In anembodiment of the invention, a BH MIMO de-mapping method involvesidentifying one or more quadrants within which the multiple vectorelements of the received signal vector, Y, are located. Accordingly, theactual constellation representation would have multiple complexdimensions, and only one complex dimension is shown in FIG. 7. FIG. 7 isillustrated in two real dimensions and for one complex signal vectorelement for the purpose of clarity of description. One of skill in theart would understand, based on the description herein, how conceptuallyto extend the depiction in FIG. 7 to apply to multi-element de-mapping.

One should understand, based on the description herein, that the QPSKvector search of equation (8) includes finding the closest QPSK vectorin the multi-dimensional MIMO symbol space as distorted by the channelmatrix H, and not just one element or element-by-element (for example,as in SIC). In fact, due to the cross-talk elements in the channelmatrix H, element-by-element minimum distance results are not likely toagree with the QPSK vector solution of equation (8). It is intended thatthe inventive subject matter encompass de-mapping of multiple elementsof a received signal vector, Y, within a multi-dimensional constellationspace. Nonetheless, FIG. 7 is useful for understanding basic concepts ofthe inventive subject matter.

Referring FIG. 7, a 16 QAM constellation 700 is shown, with an initialorigin 702 indicated roughly in the center of the constellation. Theconstellation is divided into multiple quadrants (e.g. quadrant 716).The constellation's symbols are represented by points (e.g., point 718).In one embodiment, symbols are vertically and horizontally separated bythe free Euclidian distance 704 of 2Δ. Symbols could be separated bydifferent horizontal and/or vertical distances, in other embodiments.The value of 2Δ is used for purposes of explanation, and not oflimitation.

A received signal vector is indicated by arrow 706. For ease ofdescription, the received signal vector 706 corresponds to one elementof a received signal vector, Y. As FIG. 7 illustrates, vector 706indicates a data point that is located in proximity to symbol 718.

In one embodiment, during a first iteration of a BH MIMO de-mappingmethod, a first-level QPSK search is performed to determine at least onequadrant proximate to the received signal vector 706. The “+” marks 708,710, 712, 714 indicate first-level QPSK vectors, 2Δx₀, for thefirst-level QPSK search. In the illustrated example, a QPSK vectorcorresponding to “+” mark 708 is identified as a result of thefirst-level search. “+” mark 708 identifies quadrant 716.

In one embodiment, the search space is then constricted to a reducedsearch space 720, which includes the constellation points located withinthe identified quadrant 716. The reduced search space can be representedby the QPSK constellation 720, which has a new origin 722 located in thecenter of the constellation 720. Because the constellation has beenreduced to a QPSK constellation, the constellation points now correspondto the QPSK vectors, 2Δx₁. These vectors are normalized, in oneembodiment.

The received signal vector is transformed to the new origin 722, in oneembodiment. This transformation to a new origin corresponds to theoperation of equation (7) of the pseudo-code representation, which isdescribed above. In addition, the received signal vector is scaled toaccount for the normalization of the QPSK vectors. The transformed andscaled vector is indicated as vector 724.

A lower-level QPSK search is performed, based on the reduced searchspace 720 and the transformed and scaled vector 724, to determine atleast one sub-quadrant proximate to vector 724. In the illustratedexample, a QPSK vector corresponding to constellation point 726 isidentified as a result of the lower-level search. Because this is thelowest-level search (i.e., the constellation points correspond to theQPSK vectors), constellation point 726 is identified as the de-mappedsymbol.

Constellation point 726 indicates a point that exists within reducedsearch space 720. Therefore, to identify the actual symbol within thefull constellation, a determination is made of the symbol, within theoriginal 16 QAM constellation 700, that constellation point 726corresponds to. In the illustrated example, constellation point 726corresponds to symbol 718. Accordingly, the received signal vector canbe de-mapped to symbol 718.

FIG. 7, as described above, illustrates BH MIMO de-mapping within a 16QAM constellation. The example can be expanded to lower-level orhigher-level constellations. For example, in a 64 QAM constellation, afirst-level QPSK search for a single received vector element canidentify a quadrant with 16 constellation points. The search space isreduced to the identified quadrant, a new origin is identified, the datais transformed and scaled, and a second-level QPSK search is performed.The second-level QPSK search can identify a sub-quadrant with 4constellation points. Once again, the search space is reduced to theidentified sub-quadrant, another new origin is identified, the data isagain transformed and scaled, and a third-level QPSK search isperformed. The third-level QPSK search results in the identification ofa final constellation point. The correspondence between the final pointand a symbol within the original constellation is determined, and thereceived vector element is de-mapped to the identified symbol. It wouldbe obvious to one of skill in the art, based on the description herein,how to extend the inventive subject matter to even higher-levelconstellations (e.g., 256 QAM and up).

The sequence of search operations, described above, depends only on thehierarchal nature of the QAM constellation points, and not on the bitmappings to those points. However, for certain, specific,bit-to-modulation symbol mappings, such as those illustrated in FIGS.4-6, the decisions at each level of the hierarchal search can directlyidentify specific bits.

FIG. 8 is a flowchart of a procedure for performing BH MIMO de-mapping,in accordance with an embodiment of the invention. Although theindividual operations of the procedure of FIG. 8 are illustrated anddescribed as separate operations, one or more of the individualoperations may be performed concurrently. Further, nothing requires thatthe operations be performed in the orders illustrated.

The method begins, in block 802, by performing setup calculations. Thesetup calculations are a function of H. The setup calculations can beone-time calculations, which may not be repeated as successive MIMOvector symbols are de-mapped, and which may not actually depend on thenoisy received signal vector, Y. For example, in equation (8), the Hxvalues are the same for all symbols transmitted over the same channel Hand for all levels of the hierarchal search. Thus, these Hx values canbe calculated once and stored for reuse. In addition, mathematicalmanipulations of the basic Euclidean distance in equation (8) can leadto alternative but equivalent forms of this expression, which may leadto more efficient implementations. The setup calculations of block 802may support such variants.

In block 804, a multi-antenna receiver (e.g., a MIMO receiver) producesa received signal vector, Y, of n_(R) complex de-modulation symbols,where each element of Y corresponds to a distinct receive antenna, andeach element indicates a superimposition of faded versions of n_(T)transmitted signals.

In block 806, a loop variable k is initialized to a value of 0. The loopvariable k is used to step through various levels of QPSK searches, andto indicate when the loop should terminate (e.g., when the lowest-levelQPSK search is completed).

Also in block 806, the search space for the first QPSK search isinitialized to a top-level hierarchy, by defining the top-level QPSKvector {circumflex over (x)}_(k)=0. In one embodiment, the top-levelhierarchy includes the full constellation. For example, if the elementsof the transmitted vector, x, correspond to a 16 QAM constellation, thanthe search space is initialized to a 16 QAM constellation, with anorigin at approximately the center of the constellation.

In block 808, a level-k QPSK search is performed to find {circumflexover (x)}_(k). In one embodiment, the level-k QPSK search is performedaccording to equation (8), above. The results of the search are at leasttemporarily stored.

A determination is then made, in block 810, whether k=m−1, where m isthe modulation order (e.g., m=1 for QPSK, m=2 for 16 QAM, m=3 for 16QAM, etc.). If not, then in block 812, the data elements within thereceived signal vector, Y, are transformed to a new origin and scaled tocorrespond to a reduced search space that substantially includes the oneor more quadrants identified in block 808. The data vector isnormalized, so that the next QPSK search is performed using ±1 symbols.This results in a scaled, received signal vector, {tilde over (Y)}.

Loop variable k is incremented by 1, in block 814, and the procedureiterates. In particular, block 808 is repeated, during which a level-kQPSK search is performed within the reduced search space, to find a new{circumflex over (x)}_(k).

Blocks 808, 810, 812, and 814 are repeated until it is determined, inblock 810, that k=m−1. At that time, in block 816, the results of thesearch are produced based on the lowest-level QPSK search performed, andthe method ends.

In one embodiment, the search results include “hard decisions.” Harddecisions correspond to specific indications of which bit valuescorrespond to the symbols identified in the lowest-level QPSK search.

In another embodiment, “soft decisions” are produced, which are used bya decoder (e.g., decoder 304, FIG. 3) to produce the final determinationof the bit values. In one embodiment, the soft decisions include a setof LLRs or approximations of LLRs (e.g., the difference-min-distancerule, described below, or equivalent calculations).

An approximation to the exact (log-MAP) LLR calculation is a rulereferred to as the “difference-min-difference” rule. This approximationis derived from the so-called log-MAX approximation as applied to theexact log-likelihood formula. For a given bit, b_(x), this rule is givenas equation (9):

$\begin{matrix}{{{LLR}\left( b_{x} \right)} = {\frac{1}{2\sigma_{n}^{2}}\left\{ {{\underset{{x:b_{x}} = 0}{argmin}{{Y - {Hx}}}^{2}} - {\underset{{x:b_{x}} = 1}{argmin}{{Y - {Hx}}}^{2}}} \right\}}} & (9)\end{matrix}$

where σ_(n) is the additive noise variance per element of the Y vector.

According to this embodiment, the arg min_(x:b) _(x) _(=0/1)∥Y−Hx∥²values are found and stored (e.g., in registers) as part of the QPSKsub-searches. The result is that some of the final values applied toequation (9) are true QAM constellation points, and some come fromhigher-order QPSK search results. However, the lowest-level searchescheck nearest neighbor points. Therefore, the accuracy of theseembodiments can be increased on the nearest-neighbor alternative LLRs.When the bit-value alternative is not a nearest neighbor, the LLR valuesare larger, and the decoding process is insensitive to approximationerrors in these cases.

The flowchart of FIG. 8 indicates a basic BH MIMO de-mapping method, inaccordance with one embodiment. At each level of the hierarchal search,a single QPSK vector search is performed. In other embodiments, thealgorithm is extended to include any of several tree-searchingtechniques, where multiple QPSK searches may be performed during aniteration.

Tree-searching algorithms are known, although they have not been appliedin the context of the inventive subject matter. In one embodiment, anM-algorithm tree search is incorporated into one or more levels of QPSKsearching, during which the “M” best QPSK vectors are identified forinclusion in the reduced search space for the subsequent iteration (ifany); that is, the M QPSK vectors with the smallest Euclidean distancevalues ∥Y−Hx∥. In another embodiment, a T-algorithm tree search isincorporated into one or more levels of QPSK searching, during whichthose QPSK vectors having Euclidean distance values that fall within athreshold, T, of the best QPSK vector are identified for inclusion inthe reduced search space for the subsequent iteration (if any).

FIG. 9 is an example of a tree diagram 900, which depicts atree-searching algorithm that can be incorporated into variousembodiments of the invention. Tree diagram 900 includes three levels902, 904, 906. At the root 910 of the tree, a highest-level QPSK searchis performed, to identify the W possible QPSK search values, withrespect to the received search vector Y. W indicates the number ofpossible search values at each level, or the number of “branches.”Accordingly, for the initial QPSK search at level 902, W=4^(n) ^(T) .For example, if there are n_(T)=3 transmit antennas, then there are 64branches per node in the tree. FIG. 9 illustrates the case of only 4branches per node.

At level 904, the results of the initial QPSK search are stored at nodes911, 912, 913, 914. Each node corresponds to a quadrant of the scaledQPSK constellation. Within each quadrant, in accordance with the variousembodiments, it is possible to perform a lower-level QPSK search.Accordingly, four branches extend from each node 911, 912, 913, 914, andthe tree width W=16 at this level.

At this point, it is possible to “prune” the branches to reduce thesearch. For an M-algorithm, for example, it is possible to select the Mbest nodes. For a T-algorithm, the selected nodes include the node withthe best value, and any nodes having values that fall within athreshold, T, of the best node's value. The search is continued for thebranches corresponding to the selected nodes, and the remaining branchesare pruned (i.e., the search is not continued within the correspondingquadrants).

For example, if an M-algorithm tree search is being performed with M=2,and nodes 912 and 913 include the two best values, then the search spaceis reduced to the two corresponding quadrants. Within each of thesequadrants, an additional QPSK search is performed using data that hasbeen transformed and scaled accordingly. Eight search result values areproduced, which are stored in nodes 915, 916, 917, 918, 919, 920, 921,and 922. Assuming that this is the lowest level of search, the bestresult can then be determined.

Using a tree-searching technique, one or more branches can be retainedfor lower-level QPSK searches at any or all search levels. ForM-algorithm and T-algorithm searches, respectively, the value of M or Tcan be the same at each search level, or it can change at each level.For example, using the M-algorithm, the value of M can equal two duringthe highest-level QPSK search, and that value can be reduced to one foreach subsequent, lower-level search. In other embodiments, other typesof tree-searching algorithms can be incorporated into the searchingalgorithm, as would be obvious to one of skill in the art based on thedescription herein.

Extended algorithms in accordance with various embodiments can bedescribed mathematically. Let {circumflex over (x)}_(k) ^((l)) denotethe ranked results of the level-k search, as given in equation (10):

∥{tilde over (Y)} _(k) −H{circumflex over (x)} _(k) ⁽⁰⁾∥² ≦∥{tilde over(Y)} _(k) −H{circumflex over (x)} _(k) ⁽¹⁾∥²≦  (10)

Then at level k+1, a QPSK search is performed for all level-k solutions{circumflex over (x)}_(k) ^((l)), such that equation (11) is satisfied:

∥{tilde over (Y)} _(k) −H{circumflex over (x)} _(k) ^((l))∥² ≦∥{tildeover (Y)} _(k) −H{circumflex over (x)} _(k) ^((l))∥²  (11)

where γ is the breadth parameter used in the T-algorithm. Increasing thevalue of γ expands the search space. This extended algorithm can beviewed as a tree search, which includes branch and prune aspects.

Thus, various embodiments of methods and apparatus for de-modulating andde-mapping MIMO symbols have been described. The inventive subjectmatter can be implemented in a number of different types of systems invarious embodiments, including WLAN systems, other wireless networks,terrestrial cellular telephone, satellite cellular telephone, radiosystems, paging systems, and other types of systems. Other embodimentswill be readily apparent to those of ordinary skill in the art.

The inventive subject matter is not to be construed as being limited toany particular architecture or combination of functional elements orintegrated circuits. The inventive subject matter's use is extremelyflexible, being readily adaptable to any electronic system in which itsadvantages are desired to be achieved. The systems and devices depictedin the figures are merely examples of electronic systems and devices inwhich the inventive subject matter can be used.

Many variations of the apparatus diagrams appearing in the drawings willbe apparent to those skilled in the art having the benefit of thisdisclosure. For example, although the description and figures illustrateapplication of the embodiments in systems that use 4×4 16 QAMmodulation, embodiments of the invention can be used in systems that usenumerous other modulation schemes, as well. For example, the signals maybe PAM modulation or M-PSK modulation.

The various structures of the inventive subject matter may beimplemented according to any of various elements and methods known tothose skilled in the art. There may be intermediate structure (e.g.,amplifiers, attenuators, mixers, multiplexers, inverters, buffers, etc.)or signals that are between two illustrated structures. Some conductorsmay not be continuous as illustrated, but rather they may be broken upby intermediate structure. The borders of boxes in the figures are forillustrative purposes only. An actual device would not have to includesuch defined boundaries. Further, the relative layouts of theillustrated elements are not to suggest actual relative layouts.

The various procedures described herein can be implemented in hardware,firmware or software. A software implementation could use microcode,assembly language code, or a higher-level language code. The code may bestored on one or more volatile or non-volatile computer-readable mediaduring execution or at other times. These computer-readable media mayinclude hard disks, removable magnetic disks, removable optical disks,magnetic cassettes, flash memory cards, digital video disks, Bernoullicartridges, random access memories (RAMs), read only memories (ROMs),and the like.

The foregoing description of specific embodiments reveals the generalnature of the inventive subject matter sufficiently that others can, byapplying current knowledge, readily modify and/or adapt it for variousapplications without departing from the generic concept. Therefore, suchadaptations and modifications are within the meaning and range ofequivalents of the disclosed embodiments. The phraseology or terminologyemployed herein is for the purpose of description and not of limitation.Therefore, it is manifestly intended that the inventive subject matterbe limited only by the claims and the equivalents thereof.

It is emphasized that the Abstract is provided to comply with 37 C.F.R.§1.72(b), which requires an Abstract that will allow a reader toascertain the nature and gist of the technical disclosure. The Abstractis submitted with the understanding that it will not be used tointerpret or limit the scope or meaning of the claims.

In the foregoing Detailed Description, various features are occasionallygrouped together in a single embodiment for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments of the subjectmatter require more features than are expressly recited in each claim.Rather, as the following claims reflect, inventive subject matter liesin less than all features of a single disclosed embodiment. Thus, thefollowing claims are hereby incorporated into the Detailed Description,with each claim standing on its own as a separate preferred embodiment.

1. A multiple-input multiple output (MIMO) receiver comprising: circuitry to receive a spatially-multiplexed OFDM signal through two or more antennas, the spatially-multiplexed OFDM signal having been transmitted through at least two spatial channels; demodulation and de-mapping circuitry to demodulate and de-map the received spatially-multiplexed OFDM signal to generate estimates of a transmitted signal for each of the spatial channels; and decoder circuitry to process the estimates and generate a decoded bit sequence, wherein the estimates of the transmitted signal comprise de-mapped modulation symbols.
 2. The MIMO receiver of claim 1 wherein the demodulation and de-mapping circuitry includes a symbol de-mapper for each receive signal path to process a received signal vector that includes multiple spatial-channel elements corresponding to signals received through the at least two spatial channels, and wherein each symbol de-mapper is to generate estimates of a transmit signal vector from the received signal vector for generating soft-decision values for each receive signal path.
 3. The MIMO receiver of claim 2 wherein the decoder circuitry is a MIMO decoder arranged to receive the soft decision values and generate information bits that comprise the decoded bit sequence, and wherein the MIMO decoder to receive the soft decision values from each of the symbol de-mappers after deinterleaving and multiplexing.
 4. The MIMO receiver of claim 3 wherein the demodulation and de-mapping circuitry is configured to perform a bit-hierarchical (BH) MIMO de-mapping process to generate estimates of a transmitted signal for each of the spatial channels.
 5. The MIMO receiver of claim 4 wherein the BH MIMO de-mapping process comprises demodulation of higher-order bits of received modulation symbols, cancelation of interference from the demodulated higher-order bits, reducing search space to reduce the modulation order, and a repetition of the demodulation including performance of subsequential elemental searches until the modulation order is reduced to an elemental constellation.
 6. The MIMO receiver of claim 5 wherein the elemental constellation is a BPSK constellation, and wherein QPSK 16 QAM, 64 QAM, 256 QAM constellations are higher-level constellations.
 7. The MIMO receiver of claim 3 wherein the receiver is a MMSE receiver, and wherein the demodulation and de-mapping circuitry is configured to perform minimum mean square error (MMSE) decoding to generate estimates of transmitted signals for each of the spatial channels.
 8. The MIMO receiver of claim 3 wherein the receiver is a SIC receiver, and wherein the demodulation and de-mapping circuitry is configured to perform a successive-interference cancellation (SIC) process to generate estimates of a transmitted signal for each of the spatial channels.
 9. The MIMO receiver of claim 3 wherein the demodulation and de-mapping circuitry is configured to perform a Bell Labs Layered Space-Time (BLAST) de-mapping or V-BLAST de-mapping.
 10. The MIMO receiver of claim 3 wherein the demodulation and de-mapping circuitry is configured to perform a sphere decoding process to generate estimates of a transmitted signal for each of the spatial channels.
 11. The MIMO receiver of claim 3 wherein the demodulation and de-mapping circuitry is configured to perform a maximum likelihood (ML) or reduced complexity ML process to generate estimates of a transmitted signal for each of the spatial channels.
 12. The MIMO receiver of claim 3 wherein the demodulation and de-mapping circuitry is configured to demodulate signals that were transmitted in accordance with one or more of BPSK, QPSK 16 QAM, 64 QAM, 256 QAM and higher level modulations.
 13. The MIMO receiver of claim 3 wherein the receiver is part of a hand-held wireless communication device operable in a cellular communication system.
 14. The MIMO receiver of claim 3 wherein the spatially-multiplexed OFDM signal comprises frames transmitted in accordance with a multiple-access multiplexing scheme for OFDM.
 15. A method for receiving spatially-multiplexed OFDM signals through two or more antennas in a multiple-input multiple output (MIMO) receiver, the method comprising: demodulating and de-mapping the received spatially-multiplexed OFDM signals to generate estimates of transmitted signal for each of the spatial channels; and decoding the estimates to generate a decoded bit sequence, wherein the spatially-multiplexed OFDM signal were transmitted through at least two spatial channels, and wherein the estimates of the transmitted signal comprise de-mapped modulation symbols.
 16. The method of claim 15 wherein the demodulating and de-mapping includes performing symbol de-mapping for each receive signal path to process a received signal vector that includes multiple spatial-channel elements corresponding to signals received through the at least two spatial channels, and wherein the symbol de-mapping for each receive signal path includes generating estimates of a transmit signal vector from the received signal vector for generating soft-decision values for each receive signal path.
 17. The method of claim 16 wherein the decoding comprises MIMO decoding that includes receiving the soft decision values and generating information bits that comprise the decoded bit sequence, and wherein the MIMO decoding includes to receiving the soft decision values from each of the symbol de-mapping after the deinterleaving and multiplexing.
 18. The method of claim 15 wherein the demodulation and de-mapping includes performing minimum mean square error (MMSE) decoding to generate estimates of transmitted signals for each of the spatial channels.
 19. The method of claim 15 wherein the demodulation and de-mapping includes performing a successive-interference cancellation (SIC) process to generate estimates of a transmitted signal for each of the spatial channels.
 20. The method of claim 15 wherein the demodulation and de-mapping includes performing a Bell Labs Layered Space-Time (BLAST) de-mapping or V-BLAST de-mapping.
 21. The method of claim 15 wherein the demodulation and de-mapping includes performing a sphere decoding process to generate estimates of a transmitted signal for each of the spatial channels.
 22. The method of claim 15 wherein the demodulation and de-mapping includes performing a maximum likelihood (ML) or reduced complexity ML process to generate estimates of a transmitted signal for each of the spatial channels.
 23. The method of claim 15 further comprising receiving frames that include the spatially-multiplexed OFDM signals that were transmitted in accordance with a multiple-access multiplexing scheme for OFDM.
 24. A mobile communication device for receiving multiple-input multiple output (MIMO) communications in accordance with a multiple-access multiplexing scheme for OFDM, the mobile communication device comprising: circuitry to receive a spatially-multiplexed OFDM signal through two or more antennas, the spatially-multiplexed OFDM signal having been transmitted through at least two spatial channels; demodulation and de-mapping circuitry to demodulate and de-map the received spatially-multiplexed OFDM signal to generate estimates of a transmitted signal for each of the spatial channels; and decoder circuitry to process the estimates and generate a decoded bit sequence, wherein the estimates of the transmitted signal comprise de-mapped modulation symbols, wherein the demodulation and de-mapping circuitry includes a symbol de-mapper for each receive signal path to process a received signal vector that includes multiple spatial-channel elements corresponding to signals received through the at least two spatial channels, and wherein each symbol de-mapper is to generate estimates of a transmit signal vector from the received signal vector for generating soft-decision values for each receive signal path.
 25. The mobile communication device of claim 24 wherein the decoder circuitry is a MIMO decoder arranged to receive the soft decision values and generate information bits that comprise the decoded bit sequence, and wherein the MIMO decoder to receive the soft decision values from each of the symbol de-mappers after deinterleaving and multiplexing. 